AI Intelligence Briefing Skill

You are generating a comprehensive AI Intelligence Brief for Ammar Darazanli, CTO of a healthcare technology company focused on AI-powered automation, voice AI systems, remote patient monitoring, and AI-assisted development workflows.

Your task is to research the last 14 days of AI ecosystem news and produce a single timestamped markdown file in the

news/

directory.

---

Step 0: Setup & Context Loading

1. Create the

   news/

   directory if it does not exist.
2. Generate the filename using the current timestamp:

   YYYY-MM-DD-HH-MM-SS.md

   (use

   date "+%Y-%m-%d-%H-%M-%S"

   ).
3. Compute date variables for use in all search queries throughout the brief:

   CURRENT_MONTH=$(date "+%B")         # e.g., "February"
   CURRENT_YEAR=$(date "+%Y")          # e.g., "2026"
   PREV_MONTH=$(date -v-14d "+%B")     # month from 14 days ago
   COVERAGE_START=$(date -v-14d "+%Y-%m-%d")
   COVERAGE_END=$(date "+%Y-%m-%d")
   

   These variables ensure all search queries reference the actual coverage period rather than hardcoded dates.
4. Calculate the coverage period:

   $COVERAGE_START

   through

   $COVERAGE_END

   .
5. Scan

   news/

   for the most recent existing brief. If one exists, read it in full. Extract:
   • All watchlist items and their scores
   • Categories that had thin coverage or were missing items
   • Items that need status updates
   • This informs your search strategy in Step 1.
6. If

   $ARGUMENTS

   contains a specific focus area, give it extra weight in the research and scoring. Otherwise, cover all categories equally.

Step 1: Research Phase 1 — Broad Sweep (Parallel)

Use WebSearch extensively. Launch searches in parallel batches. Perform at least 12 distinct searches covering all 7 categories below.

Date Handling in Search Queries

Use

date

to compute the current month and year dynamically — never hardcode month names or years. Before writing any search query, run:

CURRENT_MONTH=$(date "+%B")    # e.g., "February"
CURRENT_YEAR=$(date "+%Y")     # e.g., "2026"
PREV_MONTH=$(date -v-14d "+%B") # month from 14 days ago (may differ)

Then construct queries using these variables. If the coverage period spans two months, include both month names in relevant queries.

Write specific queries anchored to the coverage period, not generic ones:

• BAD: "Anthropic Claude announcements" (too vague, returns old results)
• BAD: "AI news March 2025" (hardcoded stale date)
• GOOD: "Anthropic Claude new model release features pricing {CURRENT_MONTH} {CURRENT_YEAR}"
• GOOD: "Claude Code enterprise adoption GitHub Agent HQ {CURRENT_YEAR}"
• GOOD: "healthcare voice AI startup funding Series A {CURRENT_YEAR}"
• GOOD: "Oracle Health ambient clinical AI launch {CURRENT_MONTH} {CURRENT_YEAR}"

Every search query that includes a date must use the computed current month/year or the coverage period boundaries. If a query doesn't need a date (e.g., searching for a specific product name), omit the date rather than guessing.

1.1 Major AI Labs

Search for announcements, model releases, and significant updates from:

• Anthropic (Claude models, Claude Code, API changes, enterprise features, partnerships)
• OpenAI (GPT models, ChatGPT, Codex, API changes, partnerships, security features)
• Google (Gemini models, Workspace AI, API changes, partnerships)
• Meta (LLaMA models, open-weight releases)
• xAI (Grok models, voice API, enterprise access)
• Mistral (model releases, edge deployment, pricing)
• Cohere (enterprise AI, RAG, embeddings)

1.2 AI Coding & Dev Tools

Search for updates from:

• GitHub Copilot (agent mode, features, pricing)
• Cursor (new versions, multi-agent, features)
• Windsurf (Cascade updates, Arena Mode, new models)
• Claude Code (enterprise adoption, GitHub integration, new capabilities)
• Xcode AI integrations (Claude Agent SDK, Codex)
• Devin (autonomous coding, pricing, capabilities)
• Replit Agent (new versions, autonomous workflows)
• v0 / Bolt.new / Lovable (AI app builders, vibe coding)

1.3 AI Automation Platforms

Search for updates from:

• n8n (AI agent features, HITL, new nodes)
• Make / Zapier AI (automation capabilities)
• LangChain / LangGraph (framework updates, production features)
• CrewAI (multi-agent, new versions, compliance)
• AutoGen (Microsoft, agent frameworks)
• OpenAI Agents SDK (Agent Builder, AgentKit, ChatKit)

1.4 Infrastructure & Models

Search for:

• Hugging Face (trending models, platform updates)
• Ollama (new versions, performance improvements)
• vLLM (inference optimizations)
• New open-weight models and fine-tuning breakthroughs
• NVIDIA AI inference updates
• GitHub trending AI repositories

1.5 Voice & Healthcare AI

Search for:

• Voice AI platforms (Speechmatics, Deepgram, AssemblyAI, ElevenLabs)
• Healthcare voice AI startups and funding rounds
• EHR integrations and ambient clinical AI (Oracle Health, Epic, Cerner)
• Remote patient monitoring and wearables (Validic, Philips, Masimo)
• Healthcare AI market developments and clinical AI agents

1.6 Standards & Regulation

Search for:

• MCP (Model Context Protocol) updates, new servers, security
• AI executive orders and federal policy
• HIPAA/AI guidance and enforcement
• FDA AI/ML framework updates, CDS guidance
• State AI regulation (Colorado, etc.)
• Healthcare compliance developments

1.7 Community & Research

Search for:

• GitHub trending repos (AI-tagged)
• Reddit community sentiment (r/LocalLLaMA, r/ClaudeAI, r/ChatGPT, r/MachineLearning)
• ArXiv notable papers (applied AI, agents, healthcare AI)
• Product Hunt AI launches

Step 1.5: Research Phase 2 — Targeted Follow-ups

After Phase 1, review all results and identify:

• Names, companies, or products mentioned in search results that you haven't directly searched for yet
• Categories with fewer than 2 substantive findings — do additional searches
• Items from the previous brief's watchlist that need updated status
• Funding rounds, partnerships, or launches referenced in passing that deserve their own search

Launch 6-10 additional targeted searches to fill these gaps. These should be specific and use the computed date variables where relevant:

• "Secai Voxira healthcare voice AI agent funding {CURRENT_YEAR}"
• "OpenAI Lockdown Mode ChatGPT enterprise security {CURRENT_MONTH} {CURRENT_YEAR}"
• "Apple Xcode Claude Agent SDK integration details {CURRENT_YEAR}"

Do NOT proceed to scoring until every category has at least 2 findings backed by primary sources.

Step 2: Score Each Development

For each notable development found, assign a Disruption Score (1-10):

Score Range	Meaning
1-3	Incremental improvement, nice to know
4-6	Meaningful capability change, worth evaluating within 30 days
7-8	Significant shift, should prototype or adopt within 2 weeks
9-10	Potential game-changer, immediate action recommended

Score adjustment rules:

• +1 for sustained community momentum over 48hrs
• +1 for enterprise/healthcare adoption signals
• -1 for unresolved critical bugs or broken promises
• -1 for hype fade with no real usage evidence

Step 2.5: Coverage Self-Check

Before writing the report, verify ALL of these:

• Every category (1.1-1.7) has at least 2 substantive findings
• Previous watchlist items all have updated status (if previous brief exists)
• At least 3 items are NEW (not carried from previous brief)
• You have at least 10 real, clickable URLs for the Top 10 Links section
• No item's "Impact on You" is generic filler — every bullet is specific and actionable

If any check fails, do more targeted searches before proceeding.

Step 3: Generate the Report

Write the markdown file with the following structure. Every section is required.

# AI INTELLIGENCE BRIEF — {Full Date}

**Coverage Period:** {14 days ago} - {today}
**Prepared For:** Ammar Kazanli, CTO — Healthcare Technology / AI Automation / Voice AI / Remote Patient Monitoring
**Generated:** {timestamp}

---

## TOP SCORER OF THE DAY

**{Item Name} — Score: X/10**

Why this score: {2-3 sentence justification citing specific signals — e.g., GitHub stars growth, enterprise announcements, benchmark results, community validation}

---

## MOVERS (Score changed this period)

| Item | Score | Change | Reason |
|------|-------|--------|--------|
{Items whose scores changed from previous brief. For first-time items, mark as NEW.}

---

## NEW ENTRIES

| Item | Score | What + Why It Matters |
|------|-------|-----------------------|
{All newly discovered items this period with one-line descriptions}

---

## TOP 10 LINKS I MUST VISIT TODAY

| # | Link | Why Visit | Score Context |
|---|------|-----------|---------------|
| 1 | [{descriptive title}]({URL}) | {One sentence on what you'll learn and why it matters today} | {Related item score}/10 |
| ... | ... | ... | ... |
| 10 | ... | ... | ... |

Selection criteria:
- Prioritize official announcements, release posts, and technical docs over news aggregator summaries
- Include at least 1 link from each: AI models, dev tools, healthcare AI, regulation
- Bias toward links with actionable information (APIs to try, docs to read, tools to evaluate)
- Include any link related to a score 8+ item
- Prefer primary sources (company blogs, GitHub repos, official docs) over secondary coverage

---

## WATCHLIST (All items scoring 5+, sorted by score)

| Rank | Item | Score | Trend | Status | Action By | Notes |
|------|------|-------|-------|--------|-----------|-------|
{All tracked items sorted by score descending. Trend: NEW/+N/-N/=. Status: Adopt / Prototype / Evaluate / Watch. Notes: one-line context.}

---

## DETAILED ANALYSIS BY CATEGORY

---

### 1. Major AI Labs

{For each lab with news this period:}

#### {Lab Name} — {Headline}

**Source:** {Markdown links to sources}

**What Changed:**
{Bullet list of specific changes}

**Impact on You:**
{1-3 bullets. Only include categories where impact is real and specific. Skip categories where the connection is forced.}

**Disruption Score: X/10** — {One-line action recommendation}

---

### 2. AI Coding & Dev Tools

{Same format. One sub-section per tool with significant news.}

---

### 3. AI Automation Platforms

{Same format}

---

### 4. Infrastructure & Open Models

{Same format}

---

### 5. Voice & Healthcare AI

{Same format}

---

### 6. Standards & Regulation

{Same format, with sub-sections for MCP, FDA, State regulation, HIPAA as relevant}

---

## RECOMMENDED ACTIONS

### Immediate (This Week)

{3-4 numbered actions with bold titles and one-line explanations}

### This Sprint (Next 2 Weeks)

{3-4 numbered actions}

### This Month

{3-4 numbered actions}

---

## MARKET CONTEXT

{3-5 macro observations. One bold thesis sentence each — no padding. Only include observations supported by 2+ items from this brief.}

---

## 7-DAY TREND DASHBOARD

This table tracks the **top-scoring items (7+ score)** across the last 7 days of the coverage period. Each column represents a day. The score shown is the item's disruption score on that day based on news activity. Use this to spot acceleration, sustained momentum, or fade-outs at a glance.

**How to build this table:**
1. For each item scoring 7+ in the current brief, look back through the last 7 days of the coverage period.
2. Assign a daily score based on whether significant news, releases, or developments occurred on that specific day. Use `—` if no news activity for that item on that day.
3. The "Trend" column summarizes the 7-day trajectory: `Surging` (3+ days of high activity), `Sustained` (steady presence), `Spiked` (one major day then quiet), `Building` (increasing over the week), `Cooling` (decreasing).
4. The "CTO Note" column provides a one-line actionable observation about what the trend means for decision-making.

| Item | {Day-7} | {Day-6} | {Day-5} | {Day-4} | {Day-3} | {Day-2} | {Day-1 (today)} | Trend | CTO Note |
|------|---------|---------|---------|---------|---------|---------|-----------------|-------|----------|
{Replace {Day-N} headers with actual dates (e.g., Feb 15, Feb 16, ..., Feb 21). One row per item scoring 7+. Daily scores reflect news activity on that specific day. Use — for quiet days. Trend column: Surging/Sustained/Spiked/Building/Cooling. CTO Note: one-line actionable insight.}

**Reading the dashboard:**
- **Surging items** (3+ active days) = high conviction signals, prioritize action
- **Spiked items** (single day) = may be announcement-driven, wait for follow-through before investing time
- **Sustained items** (steady across days) = durable trends worth strategic planning
- **Cooling items** = previous priorities losing momentum, consider deprioritizing

---

*Next brief: {tomorrow's date}*
*Archive items scoring below 5 after 14 days on watchlist*
*Flag any item hitting 8+ immediately — do not wait for daily brief*

Important Guidelines

• Bias toward signal over noise. Don't report minor version bumps unless they unlock new capability.
• Be honest about hype vs. substance. Miss a trend for a day rather than chase vaporware.
• Primary sources first. Prefer official blogs, changelogs, GitHub repos, and documentation over news aggregator summaries.
• Top 10 Links must be clickable. Every URL must be a real URL discovered during research. Never fabricate URLs.
• Disruption scores must be justified. Cite specific evidence (benchmarks, GitHub activity, enterprise announcements).
• No filler in "Impact on You." Only include impact categories that are genuinely relevant to the item. If an item only affects AI-assisted development, don't force a healthcare or teaching angle.
• Perform at least 18 web searches total (12+ in Phase 1, 6+ in Phase 2). Cover all 7 sub-categories.
• Track items for 14 days on the watchlist, then archive unless still scoring 5+.